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Data mining trends – year 2017

Published: June 6th, 2017

When you wish to organize large volume of data for better access, you extract them from various resources with the help of Data mining process. At the same time, with the changes in data mining trends that is happening, the major challenge for the companies will be to stay abreast with these latest updates whilst keeping in mind the most plausible solution for their data requirement.

Here, let’s take a look at some of the trend changes in data mining.

Multimedia Data Mining

Gaining popularity, multimedia data mining enables you to capture useful data precisely. Extracting data from multiple formats such as audio, text, hypertext, video, images and so on, it is converted into other formats.

Distributed Data Mining

Huge volume of data is stored in the various company locations or organizations, which are extracted using state of the art algorithms in order to deliver in depth insights and reports.

Spatial or Geographical Data Mining

Data can be mined from the environmental, astronomical and geographic data such as images clicked from outer space. These are normally used to decipher the distance and topology details, which are used for geographic information or navigation purposes.

Real time Data Mining

In an attempt to accommodate the ever increasing data load, you can find traditional data mining process is upgraded to real time data mining, so that you can better predict the future and explain the past.

Scalable and interactive data mining methods

Mining large volume of data can be challenging, but you can see that interactive data mining is considered a powerful tool of data mining, especially if addressed correctly. Same ways, scalability of data mining processes is very important, especially to help address the rapid growth in size of databases. This allows the user to arrive at the possible analysis method with interesting results, without the need for any duplication, thus saving time.

Web Mining

Here, you can see a combination of data extracted via traditional data mining method as well as data from World Wide Web. Data collected from the web is assessed using traditional data mining parameters.

Key Takeaway:

So you can see that, in these times, when data mining techniques are gaining popularity and the demand for it is on the rise, there are many companies offering data mining services, competing with which is going to be a daunting task. It is also seen that, only those companies that adapt to the changing trends and keep abreast with the latest techniques and data mining trends can survive and succeed.